MongoDB is a document-oriented, schema-free, high-performance NoSQL database. It uses dynamic queries on JSON-like documents with various data structures and scales horizontally. MongoDB is good for high-volume data, scalability, and the web. It is less suited for highly transactional or SQL-focused workloads. Documents are stored in collections and can be queried, updated, and indexed dynamically without rigid schemas.

1. open-source, high-performance,
schema-free, document-oriented
database

2. One-Size-Fits-All
No Longer
RDBMS
(Oracle, MySQL)
Non-relational
New gen. OLAP
(vertica, aster, greenplum) operational stores
(“NoSQL”)

3. NoSQL really means:
non-relational next generation
operational datastores and databases

4. Scaling out
no joins +
light transactional semantics =
horizontally scalable architectures

5. Data models
no joins +
light transactional semantics =
horizontally scalable architectures
important side effect :
new data models =
improved ways to develop
applications

6. Data Models
Key/Value
Tabular
Document-based

7. Data Models
Key/Value
memcached, dynamo, voldemort
Tabular
bigtable, cassandra, hbase, hypertable
Document-oriented
mongodb, couchdb. JSON stores

9. JSON-style documents

10. Schema-free
• Loosening constraints - added flexibility
• Dynamically typed languages
• Migrations

11. Dynamic queries
• Administration
• Ease of development
• Familiarity

12. Focus on performance

13. Replication

14. Auto-sharding

15. Many supported
platforms / languages

16. Good at
• The web
• Caching
• High volume data
• Scalability

17. Less good at
• Highly transactional
• Ad-hoc business intelligence
• Problems that require SQL

18. MongoDB Basics

19. Document
• Unit of storage (think row)
• BSON (Binary JSON)
• Represented is language dependent

20. Collection
• Schema-free equivalent of a table
• Logical groups of documents
• Indexes are per-collection

21. _id
• Special key
• Present in all documents
• Unique across a Collection
• Any type you want

22. Blog back-end

23. Post
{author: “mike”,
date: new Date(),
text: “my blog post...”,
tags: [“mongodb”, “codemash”]}

24. Comment
{author: “eliot”,
date: new Date(),
text: “great post!”}

25. New post
post = {author: “mike”,
date: new Date(),
text: “my blog post...”,
tags: [“mongodb”, “codemash”]}
db.posts.save(post)

26. Embedding a comment
c = {author: “eliot”,
date: new Date(),
text: “great post!”}
db.posts.update({_id: post._id},
{$push: {comments: c}})

27. Posts by author
db.posts.find({author: “mike”})

28. Last 10 posts
db.posts.find()
.sort({date: -1})
.limit(10)

29. Posts in the last week
last_week = new Date(2010, 0, 6)
db.posts.find({date: {$gt: last_week}})

30. Posts ending with
‘Mash’
db.posts.find({text: /Mash$/})

31. Posts with a tag
db.posts.find({tags: “mongodb”})
... and fast
db.posts.ensureIndex({tags: 1})

32. Counting posts
db.posts.count()
db.posts.find({author: “mike”}).count()

33. Basic paging
page = 2
page_size = 15
db.posts.find().limit(page_size)
.skip(page * page_size)

34. Migration: adding titles
• Easy - just start adding them:
post = {author: “mike”,
date: new Date(),
text: “another blog post...”,
tags: [“codemash”],
title: “Review from CodeMash”}
post_id = db.posts.save(post)

35. Advanced queries
• $gt, $lt, $gte, $lte, $ne, $all, $in, $nin
• where()
db.posts.find({$where: “this.author == ‘mike’”})

36. Other cool stuff
• Aggregation and map reduce
• Capped collections
• Unique indexes
• Mongo shell
• GridFS

37. • Download MongoDB
http://www.mongodb.org
• Try it out
• Let us know what you think!

38. • http://www.mongodb.org
• irc.freenode.net#mongodb
• mongodb-user on google groups
• @mongodb, @mdirolf
• mike@10gen.com
• http://www.slideshare.net/mdirolf